نشریه پژوهش های راهبردی بودجه و مالیه
پیاپی 1 (بهار 1399)

Systemic risk results from the externalities of bank distress onto the rest of the financial system or the real economy market. The purpose of this paper is investigating the impact of monetary policy on systemic risk. This paper from points of aim and method of data gathering is applied and correlation type in sequent. The required data was collected from Iranian banks in 2011-2018 period. The research model was estimated using vector error correction (VEC). The findings show long term and significant relation between monetary policy and systemic risk. Furthermore, findings show monetary policy affect systemic risk in two ways: bank's risk taking behavior and bank's balance sheet items.

The purpose of this study was to investigate whether free cash flow and corporate governance characteristics influence investment at the level of firms listed in a two-tiered strategic securities exchange. The purpose of this study is practical and the research design is quasi-experimental using post-event approach. Also, according to the nature of the research data, multivariate linear regression was used. The statistical population includes all listed companies with two-tier strategic structure, after examining the conditions using Cochran formula and probable stratified sampling, about 152 companies from different banks and financial institutions were selected as sample based on their two-tier system in the years 2009-2013. The results showed that there is a significant  and positive relationship between free cash flow and over- investment and negative relationship between free cash flow and under-investment. And the impact of reduced investment over and under through some of the features of corporate governance is far greater. Therefore, managers, analysts, and investors can be advised to consider governance factors such as the composition of shareholders and the amount of free cash flow when examining corporate financial statements.

Measuring the dynamics of the relationship between financial and non-financial industries with a systemic importance in the economy has attracted in many attention after the recent financial crisis. This paper examines conditional correlations by used models of multivariate GARCH in the ten years period among the fourteen industries with the highest market value in the capital market. The purpose of this study is to understand and identify the volatility transfer pattern among industries in order to predict financial fluctuations, as well as policy decisions and risk management to completion fundamental analysis. The results show that the "banking" industry has a positive relationship with the "pharmaceutical", "telecommunications" and "investment" industries and but also the "electricity, gas, steam and hot water" and "communications equipment" Has a negative conditional correlation.

Managers to become effective and successful in position must adapt to their job in terms of personality characteristics. For this purpose, the data of 165 firms listed in Tehran Stock Exchange for the period of 2007 to 2017 were extracted, the method to test the hypothesis was a multiple regression model and has been used a combined data model and data mining methods including neural network algorithm and decision tree. The research findings show that based on neural networks only myopia and management stability there is a significant effect on stock price crash and effect of other characteristics was not significant. The biggest effect on stock price crash based on stock negative skewness criteria was respectively related to the variables of financial leverage, the ratio of market value to book value and competition in the product market and based on volatility of stock returns criteria was related to financial leverage, return on assets and risk of return on equity. Also based on decision tree management myopia only had a significant effect on stock price crash. Based on negative skewness of stocks; stock return risk variables, management myopia and the ratio of market value to book value are respectively the biggest effect and based on volatility of stock returns criteria, the variables of stock return risk, return on assets and market value to book value ratio respectively have the most impact. Further on suggested would be considered the effect of manager’s personality characteristics on decision making of capital market stakeholders and by enactment applicable laws, consider the merit of appointing managers.

The purpose of this study was to investigate the impact of time, profitability and industry on the performance of industries accepted on the stock exchange based on Repeated Factor Designs.Repeated Factorial Designs Model is functional experiments and it is statistical model that used to the study of impact factorials. Space domain this research is Tehran Stock Exchange and Time domain this research is since (1390-1398.(Our statistical society is all four financial intermediation Activities auxiliary companies which accepted in Tehran Stock Exchange and four Transport, storage and communications companies which accepted in Tehran Stock Exchange and simple and society is equal. Research methods, descriptive and it is practical by purpose type. The results show that the effect of industry factor as well as the interaction of time, profitability and industry on company performance is significant.

The issue of performance appraisal has long been one of the important success factors in different organizations. Financial management is one of the most important sectors in public organizations. The performance of financial managers should be evaluated in terms of criteria and metrics in different areas. The purpose of the present study is to provide a model for evaluating the performance of financial managers in the public sector with particular regard to meritocracy criteria along with financial and management criteria. Structural equation approach and Smart PLS software were used to analyze the data collected through the questionnaire. The sample consisted of 62 people from the financial and managerial statistical population selected through purposive sampling. In this study, 82 measures were identified and categorized into five components: "ethical / personality traits", "management skills", "human skills" meritocracy skills" and "financial criteria". According to the findings of SmartPLS software, management skills were identified as the most important component and ethical / personality characteristics were the least important factor. The article adds to managerial research in the area of ​​evaluating the performance of financial managers in the public sector and provides a framework for evaluating the performance of financial managers in the public sector.